Area Based Crime Analysis in Spatial Data Mining Approach for Association Rule in Geo-Referenced Data

In this paper which passion to integrate a large volume of data sets into useful information by adopting a various information techniques in the most modern technology world. The adopted approaches of Single variate Association Rule for Area to Crime based on the knowledge discovery techniques such as, clustering and association-rule mining. It reveals with an inherent of patterns of information into a fruitful exploratory tool for the discovery of spatio-temporal patterns. This tool is an autonomous pattern detector to reveal plausible cause-effect associations between layers of point and area data. We present VATA algorithm with an exploratory analysis for the effectively explore geo-referenced data. The present study of this paper was focuses through the real crime dataset by using algorithm. We demonstrate approach to a new type of analysis of the spatio-temporal dimensions of records of criminal events. We hope this will lead to new approaches in the exploration of large volumes of spatio-temporal data.